Drew Johnston

I’m a Postdoctoral Research Scientist at Meta.

At Meta, I work with the Social Capital Lab, studying the connections between social ties, places, and economic opportunity.

I received my PhD in Economics in 2024 from Harvard University, where I was advised by Raj Chetty, Ed Glaeser, and Jesse Shapiro.

Before that, I studied at Columbia University, where I received a BA in Computer Science and Economics.

Working Papers

Social Ties and Residential Choice: Micro Evidence and Equilibrium Implications

with Martin Koenen

Abstract

Why don't more people move to places where they can earn higher incomes? We use individual-level data from Facebook to find that social ties play a crucial role in explaining this puzzle: social ties are concentrated locally and shape migration decisions. On average, individuals live within 100 miles of nearly 80% of their friends, with less-educated individuals having even more concentrated social networks. To establish a causal link between the location of one's friends and migration, we exploit plausibly exogenous variation in the timing of friends' moves around individuals' college graduation. Having one more friend in a given commuting zone at the time of graduation increases one's likelihood of living there by 0.3 percentage points, which is comparable in magnitude to the effect of a $470 increase in annual wages. We incorporate these findings into a spatial equilibrium model and show that the magnitude of social network effects can explain why people stay in poorer places and why less-educated people are much less responsive to economic shocks. Overall, this study shows that social networks play a first-order role --- as important or more important than canonical economic factors such as wages and rents --- in determining residential choice at the individual and aggregate level.

The Social Integration of International Migrants: Evidence from the Networks of Syrians in Germany

with Michael Bailey, Martin Koenen, Theresa Kuchler, Dominic Russel, and Johannes Stroebel
Conditionally Accepted at the Journal of Political Economy
Research Summary | Research Summary (German version) | Slides | Poster (winner, Best Poster at IC2S2 '22)

Abstract

We use de-identified friendship data from Facebook to study the social integration of Syrian migrants in Germany. We decompose the significant spatial variation in migrants’ integration levels into the rate at which Germans befriend their neighbors in general and the particular rate at which they befriend Syrian migrants versus other Germans. We follow the friending behavior of Germans that move across locations to show that both forces are more affected by local institutions and policies than persistent individual characteristics or preferences of local natives. We explore the characteristics of places with higher integration levels, and show that integration courses causally affect place-specific equilibrium integration levels by shifting the rates of Germans befriending Syrians.

Published Research

Social Networks Shape Beliefs and Behavior: Evidence from Social Distancing during the COVID-19 Pandemic

with Michael Bailey, Martin Koenen, Theresa Kuchler, Dominic Russel, and Johannes Stroebel
Journal of Political Economy Microeconomics, 2 (3), 463-494, August 2024
Press: NBER Digest
Appendix | Slides | Code | WP Version

Abstract

We analyze de-identified data from Facebook to show how social connections affect beliefs and behaviors in high-stakes settings. During the Covid-19 pandemic, individuals with friends in regions facing severe disease outbreaks reduced their mobility more than their demographically similar neighbors with friends in less affected areas. To explore why social connections shape behaviors, we show that individuals with higher friend exposure to Covid-19 are more supportive of social distancing measures and less likely to advocate to reopen the economy. We conclude that friends influence individuals’ behaviors in part through their beliefs, even when there is abundant information from expert sources.

Social Capital I: Measurement and Associations with Economic Mobility

Abstract

Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health. However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers, we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date. Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality. To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org.

Social Capital II: Determinants of Economic Connectedness

Abstract

Low levels of social interaction across class lines have generated widespread concern and are associated with worse outcomes, such as lower rates of upward income mobility. Here we analyse the determinants of cross-class interaction using data from Facebook, building on the analysis in our companion paper. We show that about half of the social disconnection across socioeconomic lines—measured as the difference in the share of high-socioeconomic status (SES) friends between people with low and high SES—is explained by differences in exposure to people with high SES in groups such as schools and religious organizations. The other half is explained by friending bias—the tendency for people with low SES to befriend people with high SES at lower rates even conditional on exposure. Friending bias is shaped by the structure of the groups in which people interact. For example, friending bias is higher in larger and more diverse groups and lower in religious organizations than in schools and workplaces. Distinguishing exposure from friending bias is helpful for identifying interventions to increase cross-SES friendships (economic connectedness). Using fluctuations in the share of students with high SES across high school cohorts, we show that increases in high-SES exposure lead low-SES people to form more friendships with high-SES people in schools that exhibit low levels of friending bias. Thus, socioeconomic integration can increase economic connectedness in communities in which friending bias is low. By contrast, when friending bias is high, increasing cross-SES interactions among existing members may be necessary to increase economic connectedness. To support such efforts, we release privacy-protected statistics on economic connectedness, exposure and friending bias for each ZIP (postal) code, high school and college in the United States at https://www.socialcapital.org.

Peer Effects in Product Adoption

Abstract

We use de-identified data from Facebook to study the nature of peer effects in the market for cell phones. To identify peer effects, we exploit variation in friends’ new phone acquisitions resulting from random phone losses. A new phone purchase by a friend has a large and persistent effect on an individual’s own demand for phones of the same brand. While peer effects increase the overall demand for phones, a friend’s purchase of a particular phone brand can reduce an individual’s own demand for phones from competing brands, in particular if they are running on a different operating system.

The Determinants of Social Connectedness in Europe

with Michael Bailey, Theresa Kuchler, Dominic Russel, Bogdan State, and Johannes Stroebel
Social Informatics 2020
Press: Facebook Research
Appendix | Replication Code | SCI Data | Slides

Abstract

We use de-identified and aggregated data from Facebook to study the structure of social networks across European regions. Social connectedness declines strongly in geographic distance and at country borders. Historical borders and unions—such as the Austro-Hungarian Empire, Czechoslovakia, and East/West Germany—shape present-day social connectedness over and above today’s political boundaries and other controls. All else equal, social connectedness is stronger between regions with residents of similar ages and education levels, as well as between regions that share a language and religion. In contrast, regionpairs with dissimilar incomes tend to be more connected, likely due to increased migration from poorer to richer regions.